PhD Dissertations - DO NOT EDIT: Recent submissions
Now showing items 21-40 of 247
-
TOWARD DIGITAL PHENOTYPING: HUMAN ACTIVITY REPRESENTATION FOR EMBODIED COGNITION ASSESSMENT
(2023-02-23)Cognition is the mental process of acquiring knowledge and understanding through thought, experience and senses. Based on Embodied Cognition theory, physical activities are an important manifestation of cognitive functions. ... -
Approximate Query Processing Using Deep Learning and Database Techniques
(2022-12-15)Data is generated at an unprecedented rate surpassing our ability to analyze them. In real applications, it is often impractical to find an exact answer by traversing the entire data. As a result, Approximate Query ... -
Understanding human actions: Cognitive assessment and action segmentation using human object interaction
(2022-11-07)Automatic understanding of human behavior has several applications in medicine and surveillance. Analysing human actions can enable cognitive assessment of children by measuring their hyperactivity and response inhibition ... -
Effective Sequence Models and Graph Neural Networks for Molecular Data Analysis
(2022-08-16)Drug discovery is the process of discovering new candidate medications. New drugs are continually developed by pharmaceutical industries to address increasing medical needs. Drug discovery involves a series of processes ... -
TOWARDS SECURITY AWARE CROWDSOURCING
(2022-08-01)Crowdsourcing has emerged as a novel problem-solving paradigm, which facilitates addressing problems by outsourcing them to the crowd. The openness of crowdsourcing renders it vulnerable to misbehaving workers that impair ... -
Towards high performance cancer staging from histology images
(2022-08-16)Digital Pathology (DP) has been recently used in replacement to traditional microscopy samples as it easy to navigate and can be analysed, processed and saved. With the invention of Digital pathology, there has been ... -
DEEP LEARNING FOR PROTEIN PROPERTY AND STRUCTURE PREDICTION
(2022-08-15)I present my work towards solving the fundamental, challenging, and valuable problem for protein property and structure prediction. Specifically, I focus on solving the problem from three critical aspects: (1) designing ... -
Semi Automatic Hand Pose Annotation using a Single Depth Camera
(2022-08-05)This thesis investigates the problem of 3D hand pose annotation using a single depth camera. While hand pose annotations are critically important for training deep neural networks, creating such reliable training data is ... -
GAN-Based Domain Translation for Hand Pose Estimation and Face Reconstruction
(2022-08-05)Deep learning solutions for hand pose estimation are now very reliant on comprehensive datasets covering diverse camera perspectives, lighting conditions, shapes, and pose variations. Since, acquiring such datasets is a ... -
HAND ANALYSIS FROM DEPTH IMAGES
(2022-08-23)Hand analysis using vision systems is necessary for interaction between people and digital devices and thus is crucial in many applications relating to computer vision and human computer interaction (HCI). The proposed ... -
MACHINE LEARNING METHODS TO IMPROVE FAIRNESS AND PREDICTION ACCURACY ON LARGESOCIALLY RELEVANT DATASETS
(2021-08-16)Machine learning-based decision support systems bring relief to the decision-makers in many domains such as loan application acceptance, dating, hiring, granting parole, insurance coverage, and medical diagnoses. These ... -
DOMAIN ADAPTIVE TRANSFER LEARNING FOR VISUAL CLASSIFICATION
(2021-08-16)Deep Neural Networks have made a significant impact on many computer vision applications with large-scale labeled datasets. However, in many applications, it is expensive and time-consuming to gather large-scale labeled ... -
MODELING FACTUAL CLAIMS WITH SEMANTIC FRAMES: DEFINITIONS, DATASETS, TOOLS, AND FACT-CHECKING APPLICATIONS
(2021-08-26)As social media sites have become major channels for the quick dissemination of news, misinformation has become a significant challenge for our society to tackle. Today fact-checking rests primarily on the shoulders of ... -
DEEP REPRESENTATION LEARNING ON GIGA-PIXEL WHOLE SLIDE IMAGES
(2020-05-21)I present my work towards solving the fundamental, challenging and valuable problem for automatically processing the giga-pixel level whole slide pathology images (WSIs): the representation of them. Specifically, I target ... -
Machine Learning Methods for Statistical Analysis and Representation Learning on Neuroimaging Data
(2022-05-17)With the recent advance and widespread adoption of imaging technological innovations, clinical practitioner and scientists can easily acquire and store a large amount of various neuroimaging modalities, such as Diffusion ... -
Designing Large-scale Key-value Systems on High-Speed Storage Devices
(2022-05-09)With the evolution of new technologies, such as edge computing, full self-driving, virtual reality, and multi-media streaming, the volume of data is growing at an accelerated speed. The global data volume could achieve ... -
UNSUPERVISED DOMAIN ADAPTATION WITH DEEP NEURAL NETWORKS
(2022-05-04)Deep neural networks (DNNs) demonstrate unprecedented achievements on various machine learning problems and applications. However, such impressive performance heavily relies on massive amounts of labeled data which requires ... -
Efficient Algorithms and Human-in-the-loop Approaches for Attribute Design and Selection
(2022-04-14)Feature engineering and feature selection are two important aspects of data science pipeline. Due to the advancement of data collection techniques in recent years, huge amount of data is becoming available in different ... -
ROBUST NOISE-BASED ATTACKS AGAINST AUDIO EVENT DETECTION SYSTEMS
(2022-04-14)The massive advances on the field of deep neural networks in the 2000 and 2010 decades led to an overwhelming adoption of these algorithms on all sorts of domains and applications. Under this widespread adoption scenario, ... -
OPTIMAL UTILITY-BASED TRAFFIC CONTROL FOR DATACENTER NETWORKS
(2022-04-05)As datacenter applications with diverse service requirements proliferate, it becomes imperative to enable datacenter network flow rate allocation that satisfies minimum user-utility requirements, while allowing for ...